nabu.app.diag_to_rot module

nabu.app.diag_to_rot.transform_images(diag, args)

Filter and transform the radios and the weights.

Filter the radios, and oversample them along the horizontal line. The method in general is similar to the composite cor finding. Several overlapping positions are used to match redundant contributions at different rotation stages ( theta and theta+180). But beforehand it is beneficial to remove low spatial frequencies. And we do oversampling on the fly.

Parameters:

• diag – object used member of diag are radios and weights

• args –

  object its member are the application parameters. Here we use only:

  low_pass, high_pass, ovs ( oversampling factor for the horisontal dimension )

nabu.app.diag_to_rot.total_merit_list(arg_tuple)

builds three lists : all_merits, all_energies, all_z_transl

For every pair (theta, theta+180 ) add an item to the list which contains: for “all_merits” a list of merit, one for every overlap in the overlap_list argument, for “all_energies”, same logic, but calculating the implied energy, implied in the calculation of the merit, for “all_z_transl” we add the averaged z_transl for the considered pair :param diag: object

used member of diag are radios, weights and zpix_transl

Parameters:

args – object containing the application parameters. Its used members are ovs, high_pass, low_pass

nabu.app.diag_to_rot.find_best_interpolating_line(args)

nabu.app.diag_to_rot.main(user_args=None)

Find the cor as a function f z translation and write an hdf5 which contains interpolable tables. This file can be used subsequently with the correct-rot utility.

nabu.app.diag_to_rot.do_height_by_height(args, overlap_list, all_diff, all_energies, all_z_transl)

nabu.app.diag_to_rot.do_linear_interpolation(args, overlap_list, all_res, all_energies, all_z_transl)